import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases





def 							UpperCAmelCase		(       lowercase				,     lowercase				):







				"""simple docstring"""



				assert isinstance(lowercase				,     lowercase				)
				assert dataset.num_rows == 4
				assert dataset.num_columns == 1
				assert dataset.column_names == ["text"]
				for feature, expected_dtype in expected_features.items():
								assert dataset.features[feature].dtype == expected_dtype





@pytest.mark.parametrize('''keep_in_memory'''				,     [False, True]				)
def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				tmp_path / '''cache'''
				__lowercase					     =				{'''text''': '''string'''}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								__lowercase					     =				TextDatasetReader(lowercase				,     cache_dir=lowercase				,     keep_in_memory=lowercase				).read()
				_check_text_dataset(lowercase				,     lowercase				)





@pytest.mark.parametrize(
    '''features'''				,     [
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]				,     )
def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				tmp_path / '''cache'''
				__lowercase					     =				{'''text''': '''string'''}
				__lowercase					     =				features.copy() if features else default_expected_features
				__lowercase					     =				(
				    Features({feature: Value(lowercase				) for feature, dtype in features.items()}				) if features is not None else None
				)
				__lowercase					     =				TextDatasetReader(lowercase				,     features=lowercase				,     cache_dir=lowercase				).read()
				_check_text_dataset(lowercase				,     lowercase				)





@pytest.mark.parametrize('''split'''				,     [None, NamedSplit('''train'''				), '''train''', '''test''']				)
def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				tmp_path / '''cache'''
				__lowercase					     =				{'''text''': '''string'''}
				__lowercase					     =				TextDatasetReader(lowercase				,     cache_dir=lowercase				,     split=lowercase				).read()
				_check_text_dataset(lowercase				,     lowercase				)
				assert dataset.split == split if split else "train"





@pytest.mark.parametrize('''path_type'''				,     [str, list]				)
def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				if issubclass(lowercase				,     lowercase				):
								__lowercase					     =				text_path
				elif issubclass(lowercase				,     lowercase				):
								__lowercase					     =				[text_path]
				__lowercase					     =				tmp_path / '''cache'''
				__lowercase					     =				{'''text''': '''string'''}
				__lowercase					     =				TextDatasetReader(lowercase				,     cache_dir=lowercase				).read()
				_check_text_dataset(lowercase				,     lowercase				)





def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase=("train",)				):







				"""simple docstring"""



				assert isinstance(lowercase				,     lowercase				)
				for split in splits:
								__lowercase					     =				dataset_dict[split]
								assert dataset.num_rows == 4
								assert dataset.num_columns == 1
								assert dataset.column_names == ["text"]
								for feature, expected_dtype in expected_features.items():
												assert dataset.features[feature].dtype == expected_dtype





@pytest.mark.parametrize('''keep_in_memory'''				,     [False, True]				)
def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				tmp_path / '''cache'''
				__lowercase					     =				{'''text''': '''string'''}
				with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
								__lowercase					     =				TextDatasetReader({'''train''': text_path}				,     cache_dir=lowercase				,     keep_in_memory=lowercase				).read()
				_check_text_datasetdict(lowercase				,     lowercase				)





@pytest.mark.parametrize(
    '''features'''				,     [
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]				,     )
def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				tmp_path / '''cache'''
				# CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
				__lowercase					     =				{'''text''': '''string'''}
				__lowercase					     =				features.copy() if features else default_expected_features
				__lowercase					     =				(
				    Features({feature: Value(lowercase				) for feature, dtype in features.items()}				) if features is not None else None
				)
				__lowercase					     =				TextDatasetReader({'''train''': text_path}				,     features=lowercase				,     cache_dir=lowercase				).read()
				_check_text_datasetdict(lowercase				,     lowercase				)





@pytest.mark.parametrize('''split'''				,     [None, NamedSplit('''train'''				), '''train''', '''test''']				)
def 							UpperCAmelCase		(       lowercase				,     lowercase				,     lowercase				):







				"""simple docstring"""



				if split:
								__lowercase					     =				{split: text_path}
				else:
								__lowercase					     =				'''train'''
								__lowercase					     =				{'''train''': text_path, '''test''': text_path}
				__lowercase					     =				tmp_path / '''cache'''
				__lowercase					     =				{'''text''': '''string'''}
				__lowercase					     =				TextDatasetReader(lowercase				,     cache_dir=lowercase				).read()
				_check_text_datasetdict(lowercase				,     lowercase				,     splits=list(path.keys()				)				)
				assert all(dataset[split].split == split for split in path.keys()				)
def 							UpperCAmelCase		(       lowercase				,     lowercase				):







				"""simple docstring"""



				__lowercase					     =				word.split()

				def justify(lowercase				,     lowercase				,     lowercase				) -> str:
								__lowercase					     =				max_width - width
								__lowercase					     =				len(lowercase				)
								if len(lowercase				) == 1:
												# if there is only word in line
												# just insert overall_spaces_count for the remainder of line
												return line[0] + " " * overall_spaces_count
								else:
												__lowercase					     =				words_count - 1
												# num_spaces_between_words_list[i] : tells you to insert
												# num_spaces_between_words_list[i] spaces
												# after word on line[i]
												__lowercase					     =				spaces_to_insert_between_words * [
												    overall_spaces_count // spaces_to_insert_between_words
												]
												__lowercase					     =				(
												    overall_spaces_count % spaces_to_insert_between_words
												)
												# distribute spaces via round robin to the left words
												for i in range(lowercase				):
																num_spaces_between_words_list[i] += 1
												__lowercase					     =				[]
												for i in range(lowercase				):
																# add the word
																aligned_words_list.append(line[i]				)
																# add the spaces to insert
																aligned_words_list.append(num_spaces_between_words_list[i] * ''' '''				)
												# just add the last word to the sentence
												aligned_words_list.append(line[-1]				)
												# join the aligned words list to form a justified line
												return "".join(lowercase				)

				__lowercase					     =				[]
				__lowercase					     =				[]
				__lowercase					     =				0
				for word in words:
								if width + len(lowercase				) + len(lowercase				) <= max_width:
												# keep adding words until we can fill out max_width
												# width = sum of length of all words (without overall_spaces_count)
												# len(word) = length of current word
												# len(line) = number of overall_spaces_count to insert between words
												line.append(lowercase				)
												width += len(lowercase				)
								else:
												# justify the line and add it to result
												answer.append(justify(lowercase				,     lowercase				,     lowercase				)				)
												# reset new line and new width
												__lowercase     ,	__lowercase					     =				[word], len(lowercase				)
				__lowercase					     =				max_width - width - len(lowercase				)
				answer.append(''' '''.join(lowercase				) + (remaining_spaces + 1) * ''' '''				)
				return answer


if __name__ == "__main__":
		from doctest import testmod

		testmod()